Genetic analysis of probable sleep bruxism and its associations with clinical and behavioral traits

被引:9
作者
Strausz, Tommi [1 ]
Strausz, Satu [1 ,2 ]
FinnGen
Palotie, Tuula [3 ,4 ]
Ahlberg, Jari [3 ]
Ollila, Hanna M. [1 ,5 ,6 ,7 ,8 ,9 ]
机构
[1] Univ Helsinki, Inst Mol Med Finland, Helsinki Inst Life Sci, Helsinki, Finland
[2] Stanford Univ, Dept Genet, Sch Med, Stanford, CA USA
[3] Helsinki Univ Hosp, Head & Neck Ctr, Dept Oral & Maxillofacial Dis, Helsinki, Finland
[4] Univ Helsinki, Fac Med, Dept Oral & Maxillofacial Dis, Orthodont, Helsinki, Finland
[5] Broad Inst & Harvard, Cambridge, MA USA
[6] Massachusetts Gen Hosp, Ctr Genom Med, Boston, MA USA
[7] Massachusetts Gen Hosp, Anesthesia Crit Care & Pain Med, Boston, MA USA
[8] Harvard Med Sch, Boston, MA USA
[9] Univ Helsinki, Inst Mol Med Finland, Helsinki Inst Life Sci, PL 20 Tukholmankatu 8, Helsinki 00014, Finland
关键词
Sleep Bruxism; Genome-Wide Association Study; Population Register; FinnGen; Temporomandibular Joint Dysfunction Syndrome; Pain; Gastroesophageal Reflux; Obstructive Sleep Apnea; RISK-FACTORS; GENOME-WIDE; RETINA; ADULTS;
D O I
10.1093/sleep/zsad107
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Study Objectives Sleep bruxism (SB) can cause damage on teeth, headache and severe pain affecting both sleep and daily functioning. Yet despite the growing interest into bruxism, the underlying clinically relevant biological mechanisms remain unresolved. The aim of our study was to understand biological mechanisms and clinical correlates of SB including previously reported disease associations. Methods We used data from the FinnGen release R9 (N = 377 277 individuals) that are linked with Finnish hospital and primary care registries. We identified 12 297 (3.26%) individuals with International Classification of Diseases (ICD)-10 codes used for SB. In addition, we used logistic regression to examine the association between probable SB and its clinically diagnosed risk factors and comorbidities using ICD-10 codes. Furthermore, we examined medication purchases using prescription registry. Finally, we performed the first genome-wide association analysis for probable SB and computed genetic correlations using questionnaire, lifestyle, and clinical traits. Results The genome-wide association analysis revealed one significant association: rs10193179 intronic to Myosin IIIB (MYO3B) gene. In addition, we observed phenotypic associations and high genetic correlations with pain diagnoses, sleep apnea, reflux disease, upper respiratory diseases, psychiatric traits, and also their related medications such as antidepressants and sleep medication (p < 1e-4 for each trait). Conclusions Our study provides a large-scale genetic framework to understand risk factors for SB and suggests potential biological mechanisms. Furthermore, our work strengthens the important earlier work that highlights SB as a trait that is associated with multiple axes of health. As part of this study, we provide genome-wide summary statistics that we hope will be useful for the scientific community studying SB.
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页数:10
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